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README.md

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+MLE-Dojo is a Gym-style framework for systematically training, evaluating, and improving autonomous large language model (LLM) agents in iterative machine learning engineering (MLE) workflows. 
+Unlike existing benchmarks that primarily rely on static datasets or single-attempt evaluations, MLE-Dojo provides an interactive environment enabling agents to iteratively experiment, debug, and refine solutions through structured feedback loops. Built upon 200+ real-world Kaggle challenges (e.g., tabular data analysis, computer vision, natural language processing, and time series forecasting). MLE-Dojo covers diverse, open-ended MLE tasks carefully curated to reflect realistic engineering scenarios such as data processing, architecture search, hyperparameter tuning, and code debugging.
+Its fully executable environment supports comprehensive agent training via both supervised fine-tuning and reinforcement learning, facilitating iterative experimentation, realistic data sampling, and real-time outcome verification.